Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Huang, Tianjian"'
Differential privacy (DP) ensures that training a machine learning model does not leak private data. In practice, we may have access to auxiliary public data that is free of privacy concerns. In this work, we assume access to a given amount of public
Externí odkaz:
http://arxiv.org/abs/2306.15056
As deep learning (DL) efficacy grows, concerns for poor model explainability grow also. Attribution methods address the issue of explainability by quantifying the importance of an input feature for a model prediction. Among various methods, Integrate
Externí odkaz:
http://arxiv.org/abs/2202.11912
Autor:
Huang, Tianjian, Halbe, Shaunak, Sankar, Chinnadhurai, Amini, Pooyan, Kottur, Satwik, Geramifard, Alborz, Razaviyayn, Meisam, Beirami, Ahmad
While deep learning through empirical risk minimization (ERM) has succeeded at achieving human-level performance at a variety of complex tasks, ERM is not robust to distribution shifts or adversarial attacks. Synthetic data augmentation followed by e
Externí odkaz:
http://arxiv.org/abs/2110.11205
Publikováno v:
Signal Processing Volume 189, December 2021, 108245
Min-max saddle point games have recently been intensely studied, due to their wide range of applications, including training Generative Adversarial Networks (GANs). However, most of the recent efforts for solving them are limited to special regimes s
Externí odkaz:
http://arxiv.org/abs/2106.06075
Quantization of the parameters of machine learning models, such as deep neural networks, requires solving constrained optimization problems, where the constraint set is formed by the Cartesian product of many simple discrete sets. For such optimizati
Externí odkaz:
http://arxiv.org/abs/2009.03482
Autor:
Razaviyayn, Meisam, Huang, Tianjian, Lu, Songtao, Nouiehed, Maher, Sanjabi, Maziar, Hong, Mingyi
Publikováno v:
IEEE Signal Processing Magazine (Volume: 37, Issue: 5, Sept. 2020)
The min-max optimization problem, also known as the saddle point problem, is a classical optimization problem which is also studied in the context of zero-sum games. Given a class of objective functions, the goal is to find a value for the argument w
Externí odkaz:
http://arxiv.org/abs/2006.08141
Recent applications that arise in machine learning have surged significant interest in solving min-max saddle point games. This problem has been extensively studied in the convex-concave regime for which a global equilibrium solution can be computed
Externí odkaz:
http://arxiv.org/abs/1902.08297
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.